Peer review process
Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, public reviews, and a provisional response from the authors.
Read more about eLife’s peer review process.Editors
- Reviewing EditorAdrien PeyracheMcGill University, Montreal, Canada
- Senior EditorLaura ColginUniversity of Texas at Austin, Austin, United States of America
Reviewer #1 (Public review):
Summary:
NPAS4 is an activity-dependent transcription factor that regulates inhibitory synapses onto active pyramidal neurons. In this study, the authors examined whether this molecular mechanism influences neural coding in awake animals. To accomplish this, they generated a sparse, CA1-specific NPAS4 knockout in mice and compared knockout neurons with neighboring wild-type neurons recorded from the same animals during navigation. They found that, although neurons lacking NPAS4, which received diminished somatic inhibition and enhanced dendritic inhibition, still encoded location, their spatial firing was less precise: place fields were broader and less stable, showed weaker firing within the field, and exhibited more firing outside the field. KO neurons also exhibited poorer temporal organization with weaker coupling to theta oscillations and reduced phase precession, two signatures of precise spike timing in the hippocampus. Overall, the study suggests that NPAS4 links the balance of somatic and dendritic inhibition to the quality of circuit-level coding by refining the spatial and temporal precision of neuronal firing.
Strengths:
Using a sparse CA1-specific knockout, the authors compared NPAS4-deficient neurons with neighboring wild-type neurons within the same animal and network. This is a significant advantage because it minimizes confounding factors arising from global circuit disruption, providing a clearer comparison of genotypes. Furthermore, the rigorous optogenetic tagging strategy used to distinguish KO from WT neurons in vivo makes the single-cell comparisons much more convincing. Electrophysiological recordings from intermingled WT and KO neurons enable precise spike-timing measurements relative to a shared local field potential, which would be challenging to obtain with calcium imaging.
Weaknesses:
Rather than an acute manipulation, the authors rely on a chronic, sparse knockout, and NPAS4 had been deleted for at least one month before recording. Consequently, while the paper demonstrates a robust long-term phenotype, it is less definitive about the immediate causal sequence by which NPAS4 induction alters inhibition and reshapes spatial and temporal coding. Furthermore, the study focuses on single-neuron coding during navigation and does not test whether the observed degradation in coding precision leads to corresponding impairments in learning or memory in the same animals. In the discussion, the authors suggest that NPAS4 may be especially important for ripple-associated activity during sleep; however, the paper does not test this possibility.
Reviewer #2 (Public review):
Summary:
The manuscript by Payne and colleagues examines how cell-autonomous loss of the activity-dependent transcription factor NPAS4 reshapes spatial and temporal coding in CA1 pyramidal neurons of behaving mice. The work builds on the Bloodgood lab's established framework in which NPAS4 reorganizes inhibition along the somatodendritic axis of CA1 pyramidal cells, principally by regulating CCK+ basket cell synapses, and asks whether this transcriptionally driven reconfiguration of inhibition propagates into the spike-train statistics that underlie hippocampal function. The combination of sparse Cre delivery with channelrhodopsin-mediated optotagging in Npas4 fl/fl:Ai32 mice is technically elegant, as it permits within-animal comparisons of intermingled wild-type and knockout pyramidal neurons sharing a common LFP, which is a significant analytical advantage for spike-timing analyses and for controlling network-level confounds. The reported phenotype is internally consistent and converges on a coherent story: knockout neurons exhibit broader and less stable place fields, lower signal-to-noise within fields, increased out-of-field activity, weaker theta-phase coupling, and shallower phase precession slopes, with the temporal deficits at least partly explained by enlargement of the spatial receptive field.
Strengths:
Several aspects of the work deserve explicit recognition. The validation of the optotagging strategy is thorough, including the high-power stimulation control to corroborate WT classification and the post hoc histological alignment of GFP+ density with electrophysiologically identified KO fractions. The decision to test NPAS4 function in adult mice maintained in long-term enriched environments addresses an important gap, since most prior work has focused on juveniles or short-term induction paradigms. The acute slice recordings recapitulating the somatodendritic inhibition phenotype reassure the reader that the in vivo measurements are interpreted against a known synaptic substrate. The analytical framework, especially the difference maps across epochs and the linear regression decomposition of phase precession slope into genotype, field size, and theta modulation strength, is rigorous and goes beyond simple group-level comparisons. The conceptual contribution, namely the demonstration that an activity-dependent transcription factor can be tied to single-neuron coding properties in vivo, is meaningful, although it is fair to note that the direction of the effect, given that the CCK to place cell link and the NPAS4 to CCK link have each been established in prior independent studies, is largely along the lines one would predict.
Weaknesses:
The most consequential concern, in my view, is the experimental context in which the entire study is conducted. Every animal is housed in an enriched environment for two to three months, and Figure 1A itself shows that NPAS4 expression in CA1 is essentially undetectable in standard-environment conditions and only emerges with enrichment. This raises the question of whether the manuscript is in fact describing the function of NPAS4 in general, or the function of NPAS4 specifically as recruited by chronic enrichment. The paper, in its current framing, elides this distinction and presents the EE state as if it were the baseline, which it is not. EE is known to alter hippocampal connectivity, the dynamics of place cell ensembles, and the expression of many activity-dependent genes; the CCK to pyramidal cell connectivity that the authors invoke as the mechanistic anchor is also dense in standard housing, so the absence of detectable NPAS4 in SE conditions raises the further conceptual problem of how NPAS4-negative neurons would normally be innervated by CCK+ basket cells in the first place. A direct comparison of WT and KO neurons in standard-environment animals, even on a smaller scale, would discriminate between two very different interpretations, namely that NPAS4 has a constitutive role in tuning CA1 firing versus that it is specifically engaged by enrichment-driven activity and contributes to an EE-specific reorganization of coding. Recent work, including Chiaruttini and colleagues (2025), reports baseline NPAS4 expression in CA1, so the SE result in Figure 1A may itself underestimate normal expression and deserves further scrutiny. Without an SE comparison, the generality of the conclusions cannot be assessed, and the title and abstract risk overstating the scope of the findings, particularly when one considers that NPAS4 is also induced by contextual fear conditioning and other paradigms, which would predict context-specific effects rather than a uniform refinement function.
A closely related concern is the meaning of the knockout itself. Even under EE, only a few percent of CA1 pyramidal neurons express detectable NPAS4 at any given moment (Figure 1A), yet the AAV strategy deletes the gene in 30 to 60 percent of pyramidal neurons. In effect, the majority of cells classified as KO in this study would not have been expressing the protein under the relevant conditions, so the population that is statistically driving the WT versus KO differences must include a non-trivial fraction of neurons in which the deletion has no protein-level consequence. This dilutes the expected effect and raises a more interesting biological question: are the observed phenotypes carried by the few KO neurons that would have expressed NPAS4, or do they emerge from a constitutive function of the gene that is broader than the IHC signal suggests? An additional, related possibility is that NPAS4 expression segregates non-uniformly across functional classes, for example, concentrating in cells with particular firing-rate or spatial-tuning profiles, in which case the "KO" label is binary at the level of the manipulation but graded at the level of biological consequence. Stratifying the KO population by some proxy of activity history, or relating the magnitude of the phenotype to per-cell measures of recent firing, would help address this. As written, the manuscript treats the KO designation as homogeneous, while the underlying biology is almost certainly not.
A third concern, more conventionally statistical, is the treatment of cells as independent observations. The analyses rely almost uniformly on Kolmogorov-Smirnov tests applied to individual units pooled across animals, but cells recorded in the same animal share not only a common subject but a common network, since WT and KO neurons here are intermingled in the same CA1 microcircuit. Cell numbers per animal range widely, so a mixed-effects framework treating animal as a random factor, or a hierarchical bootstrap, would clarify which effects are robust against animal-level and session-level variability and protect against pseudo-replication. This concern is particularly acute for the smaller effects in Figure 2C-E, where the cumulative distributions overlap substantially, and the differences could plausibly be driven by a small number of mice or sessions. In several figures, the individual dots in supplementary panels are not labeled by animal or session, and that information would be useful for assessing how much of each effect is carried by which subset of the cohort.
The absence of a Cre/ChR2 expression control is a separate gap. The comparison throughout the manuscript pits Cre+ ChR2+ neurons (NPAS4 KO) against neighboring non-transduced neurons (WT). This is internally elegant, but leaves open the possibility that part of the phenotype arises from chronic ChR2 expression or constitutive Cre activity rather than from NPAS4 loss, especially given that most of the readouts are subtle. A small companion cohort of Ai32 mice without the floxed Npas4 allele, injected with the same AAV and processed through identical optotagging and electrophysiology pipelines, would address this definitively and is, in my view, a near-essential addition.
Several of the downstream phenotypes would benefit from stratified comparisons that hold first-order properties constant. Many of the downstream differences (stability across epochs, theta coupling, phase precession) could, in principle, be inherited from the upstream difference in firing rate, since the high-firing and high-spatial-information cells in the WT pool are likely contributing disproportionately to the group statistics. The authors do perform firing-rate-matched controls in Figure S4D-G, which is helpful, but the analysis should be extended in two ways: a parallel stratification by spatial information for the stability analyses in Figure 4, and matched comparisons of theta coupling (Figure 5) and phase precession (Figure 6) on neurons drawn from overlapping firing-rate and spatial-information distributions. The regression decomposition for phase precession is a step in this direction and shows that field size, not genotype, is the dominant predictor of slope; this finding, in my reading, deserves more prominent framing in the discussion than it currently receives, since it implies that the temporal precision phenotype is largely downstream of the spatial one rather than a parallel deficit.
The place field stability analysis is interesting but somewhat under-analyzed. The authors show that KO fields shift toward the field entrance more rapidly than WT fields and propose that this reflects an accelerated or dysregulated Mehta-effect-like dynamic. The framing is attractive, but the analysis does not establish that the shifts are systematic in the same way the classical Mehta effect is. An alternative reading is that the elevated out-of-field firing creates spurious local maxima that the peak-finding procedure occasionally classifies as field shifts, especially when in-field firing is reduced. A control analysis using a fixed reference window around the original peak, rather than re-identifying the peak each epoch, would help distinguish a genuine plasticity-like shift from instability driven by noise. The behavior of the WT population in epoch 4 also raises a question: would the drift intensify over longer recording windows, and to what extent is the apparent drift imposed by the repetitive structure of the task itself, in which animals are effectively running on a constrained linear /circular track that may impose drift-like dynamics across the population independently of genotype?
A final note on mechanism. The manuscript leans on prior work showing that NPAS4 regulates CCK+ basket cell synapses, and uses this as the mechanistic anchor for the coding deficits. The connection is reasonable but remains indirect within this study, since the authors do not measure CCK+ interneuron activity, perisomatic inhibition, or local circuit dynamics in the same animals. The discussion already acknowledges some of this, but the speculative framing of dendritic versus somatic inhibition contributions could be tightened, especially given that competing inhibitory sources (PV+ basket cells, axo-axonic cells, OLM interneurons) also shape the spatial and temporal features measured here. A more cautious mechanistic framing, distinguishing what is demonstrated from what is inferred from prior work, would be appropriate.
In summary, this is an ambitious and technically demanding study that makes a meaningful contribution by linking activity-dependent transcriptional regulation of inhibition to the spatial and temporal organization of CA1 spike trains in awake, behaving mice. The within-animal optotagging design is a real strength, the phenotype is internally consistent across multiple coding metrics, and the conceptual implications for how experience tunes single-neuron coding are significant. The principal concerns, namely the unaddressed enrichment confound that pervades the entire dataset, the conceptual ambiguity around what a KO designation actually means at the cell level when only a small fraction of CA1 neurons express the protein, the statistical treatment of nested observations from a shared microcircuit, the missing transgene control, the absence of stratified comparisons by firing rate and spatial information for the secondary phenotypes, and the somewhat overreaching mechanistic framing of the discussion, are all addressable, and if handled carefully would substantially strengthen the manuscript. With these revisions, the work would be a valuable contribution to the literature on how the molecular memory of activity shapes circuit-level coding.